最优滑动平均滤波器及其在自校正控制中用于克服确定性干扰

    Optimal Moving Average Filter with Application to Self-Tuning Control against Deterministic Disturbances

    • 摘要: 从确定性干扰的内模观点导出了适用于线性随机受控对象的最优滑动滤波器。这使最小方差自校正控制器不仅能有效地克服各种可用线性齐次差分方程模型描述的确定性干扰(如阶跃式和正弦振荡式干扰等),而且还可很好地抑制系统中随机噪声的放大作用。从而,辨识精度和控制质量部得以改进(特别是在较强的有色噪声情况下)。

       

      Abstract: The optimal moving average filter for the linear stochastic controlled plant is developed from the viewpoint of the internal model of the deterministic disturbance. filter enables the minimum-variance self-tuning control not only to effectively overcome various kinds of deterministic disturbances modelled by linear homogeneous difference equation, such as stepwise and sinusoidal disturbances, but also to greatly depress the amplification of the random noise in the control system. Thus,both the precisions of identification and the quality of control can be improved (especially in the cases of strong colored noises).

       

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